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Estimators for the difference in means/medians (2 related samples)

Estimators for the difference in means/medians of related samples and their properties and assumptions.

Estimator Purpose
Mean difference Estimate the difference between the means.
Standardized mean difference Estimate the standardized difference between the means.

Cohen's d is the most popular estimator using the difference between the means divided by the pooled sample standard deviation. Cohen's d is a biased estimator of the population standardized mean difference (although the bias is very small and disappears for moderate to large samples) whereas Hedge's g applies an unbiasing constant to correct for the bias.

Median difference Estimate the median of the differences.
Hodges-Lehmann location shift Estimate the shift in location.

A shift in location is equivalent to a difference between means/medians when the distribution of the differences is symmetric. Symmetry is quite often inherently satisfied for paired data.

Related concepts
Difference between means/medians effect size
Related tasks
Estimating the difference between means/medians
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Version 6.15
Published 18-Apr-2023
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